{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 0 - 数据探索与准备\n",
    "\n",
    "## 综述\n",
    "\n",
    "本项目的目标是基于由摄影机图片和车辆上一个时刻已知的状态训练一个深度学习模型预测汽车转向角。在这个文本里，我们将为我们的端对端深度学习模型准备数据。沿着这个思路，我们也将做一些关于数据集的观测（可视化），这些观测将在训练模型的时候帮助我们。\n",
    "\n",
    "\n",
    "## 什么是端对端深度学习（End-to-End Deep Learning）？\n",
    "\n",
    "端对端深度学习（End-to-End Deep Learning）是一种反映成功构建深度神经网络的建模策略。不同于传统手段，这种策略不是基于特征工程（*译者：传统的机器学习方法需要对数据手工进行特征提取。*）。而是借助深度神经网络的力量，伴随着当前硬件（比如GPUs FPGAs）的发展来加强大数据不可思议的潜能。这相比于传统的机器学习更接近于人类的学习方法，因为它让神经网络将原始输入直接映射到输出。这种方法的一个很大的缺点就是它需要非常大的训练数据量，这使得它不适用于许多常见的应用程序。因为模拟器能能产生无穷多的数据，他们对于端对端深度学习算法是一种完美的数据来源。如果你想学习更多，这个Andrew Ng的[视频](https://www.coursera.org/learn/machine-learning-projects/lecture/k0Klk/what-is-end-to-end-deep-learning)将给你一个很棒的介绍。\n",
    "\n",
    "自动驾驶是一个能从端对端深度学习力量中受益很大的领域。为了达到SAE 等级4 的自动驾驶，汽车需要从大量数据中来进行训练（对于汽车制造商来说，他们不太可能每周来收集数以百计的千兆数据）， 事实上这些数据如果没有模拟器不可能收集到。\n",
    "\n",
    "使用逼真的模拟器，比如[AirSim](https://github.com/Microsoft/AirSim), 能使得没有实际测试车的情况下收集大量数据进行无人驾驶模型训练成为可能。这些数据可以之后使用相对较少的实车收集数据进行fine-tune。这个技术被称为行为克隆。在这份文档里，你将仅通过使用一个正向的网络摄像头作为输入训练一个模型，根据在AirSim 中的一部分地景图来学习怎样使汽车转向。我们的策略是做一些基础的数据分析来使得读者对数据有一些认识，然后训练一个端对端深度学习模型通过网络摄像头给出的数据流来预测正确的转向控制信号（也就是“转向角”）以及汽车目前的状态参数（速度，转向角，油门等）。\n",
    "\n",
    "这之前，请保证你已经下载了我们将要用到的数据集。如果你没看readme 文件中的说明书，你可以在[这里](https://aka.ms/AirSimTutorialDataset)下载。\n",
    "\n",
    "现在大家开始导入一些有用的标准库。\n",
    "\n",
    "**注意：如果你在这份文档中的注释里看到了一些文字在<< ...... >> 里，这说明这部分代码你需要做一些必要的适配性调整才能运行。**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import h5py\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image, ImageDraw\n",
    "import os\n",
    "import Cooking\n",
    "import random\n",
    "\n",
    "# << 将其指向包含原始数据的目录 >>\n",
    "RAW_DATA_DIR = 'data_raw/'\n",
    "\n",
    "# << 将其指向所期望的输出(.h5)数据的目录 >>\n",
    "COOKED_DATA_DIR = 'data_cooked/'\n",
    "\n",
    "# 在RAW_DATA_DIR 目录下存放了数据被搜索的文件夹\n",
    "# 举例来说，第一个被搜索到的文件夹是RAW_DATA_DIR/normal_1\n",
    "DATA_FOLDERS = ['normal_1', 'normal_2', 'normal_3', 'normal_4', 'normal_5', 'normal_6', 'swerve_1', 'swerve_2', 'swerve_3']\n",
    "\n",
    "# 本文档中图片的大小\n",
    "FIGURE_SIZE = (10,10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先，我们来看看原始数据。原始数据分为两部分 - 图片和.tsv 格式文件。首先让我们来读一下.tsv 格式文件。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Speed (kmph)</th>\n",
       "      <th>Throttle</th>\n",
       "      <th>Steering</th>\n",
       "      <th>Brake</th>\n",
       "      <th>Gear</th>\n",
       "      <th>ImageName</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>93683464</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_0.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>93689595</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_1.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_2.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_3.png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_4.png</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Timestamp  Speed (kmph)  Throttle  Steering  Brake Gear  ImageName\n",
       "0   93683464             0       0.0  0.000000    0.0    N  img_0.png\n",
       "1   93689595             0       0.0  0.000000    0.0    N  img_1.png\n",
       "2   93689624             0       0.0 -0.035522    0.0    N  img_2.png\n",
       "3   93689624             0       0.0 -0.035522    0.0    N  img_3.png\n",
       "4   93689624             0       0.0 -0.035522    0.0    N  img_4.png"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_tsv_path = os.path.join(RAW_DATA_DIR, 'normal_1/airsim_rec.txt')\n",
    "sample_tsv = pd.read_csv(sample_tsv_path, sep='\\t')\n",
    "sample_tsv.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这个数据集包含了标注，也就是转向角。它也有转向角被纪录时刻拍下来对应的图片。我们来看一张样板图片 - 'img_0.png'， 它在 'normal_1' 文件夹下（之后会有更多关于文件夹的命名介绍）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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kbJBlposYeSYAEqgbZwVUdQ2Csj5qqDL254XfQ6gq5Qe4WG0Vvs/OF6A0FkbX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2reAVxMr7meb9BfnS+9FbO/4xuPItuyyMqOy7n6Xn/hp77BncND2rYz51vVLRJpPicvStJ8O+aa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xNZ+H9nwAmEzGUefc89SFCKs2pZoRQ0x57PQzOPqM0IWHdpyMOH4apgTNdn8QzEpJHaYEKDqO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\nWmllm8v/B8A1YkKbpW1yAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x4d62ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_image_path = os.path.join(RAW_DATA_DIR, 'normal_1/images/img_0.png')\n",
    "sample_image = Image.open(sample_image_path)\n",
    "plt.title('Sample Image')\n",
    "plt.imshow(sample_image)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以立刻注意到，这张图片**只有一部分图片内容是我们感兴趣的**。 举例来说，我们应该能仅仅通过图片中的感兴趣部分(ROI, 下图中红色方框中部分)决策让汽车如何转向。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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swWiQ2zaqmxZl1WBdKqY8GeVYrGsQpFcyt2tVSuDkbIk8E1itVbMxgIOdMQ52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\nltNLtRD+6m9+i7/0018miWLjVuk4SkjSP/xpVnB2M8N3+lQ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HYdIzd1ziMOL2sWKdeK6j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Mt896rMTSFVVbUab3pR69qWJIlUY1nDh+t0xTpdGWtwx5KcP37/Tw9GPxiN5Bf/7FcBcPyQJI65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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b1510f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample_image_roi = sample_image.copy()\n",
    "\n",
    "fillcolor=(255,0,0)\n",
    "draw = ImageDraw.Draw(sample_image_roi)\n",
    "points = [(1,76), (1,135), (255,135), (255,76)]\n",
    "for i in range(0, len(points), 1):\n",
    "    draw.line([points[i], points[(i+1)%len(points)]], fill=fillcolor, width=3)\n",
    "del draw\n",
    "\n",
    "plt.title('Image with sample ROI')\n",
    "plt.imshow(sample_image_roi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**提取ROI 将既能减少训练时间，也能减少训练该模型所需要的数据**。 它也将使得模型不去关注环境中无关的特征（例如云， 鸟， 等）\n",
    "\n",
    "另外我们也能观测到**数据集展现了一个垂直翻转误差**。 也就是说，如果我们绕着Y 轴翻转，并且我们同时也翻转转向的方向，我们得到一个有效数据点。这很重要因为它能使得我们的有效数据翻倍。\n",
    "\n",
    "另外，**训练模型在不同光照条件下也应该不变**，所以我们能够通过全局放大图片的亮度产生额外的数据。\n",
    "\n",
    "\n",
    "> **思考训练 0.1：**  \n",
    "一旦你完成了本文档，作为训练，你应该要试着用上面三种方法去处理没有被加工过的数据，使用控制变量法。你看到结果有很大不同了么？\n",
    "\n",
    "> **思考训练 0.2**  \n",
    "我们在Readme 文档中指出，端对端深度学习消除了在输入数据给学习算法之前的手动特征工程。你有考虑过主动给原始数据做一些预处理当作特征处理呢？为什么或为什么不？\n",
    "\n",
    "\n",
    "现在，让我们集合所有的非图片数据到一个数据流来获得更多的一些信息。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of data points: 46738\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Speed (kmph)</th>\n",
       "      <th>Throttle</th>\n",
       "      <th>Steering</th>\n",
       "      <th>Brake</th>\n",
       "      <th>Gear</th>\n",
       "      <th>ImageName</th>\n",
       "      <th>Folder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>93683464</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_0.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>93689595</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_1.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_2.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_3.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>93689624</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.035522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>N</td>\n",
       "      <td>img_4.png</td>\n",
       "      <td>data_raw/normal_1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Timestamp  Speed (kmph)  Throttle  Steering  Brake Gear  ImageName  \\\n",
       "0   93683464             0       0.0  0.000000    0.0    N  img_0.png   \n",
       "1   93689595             0       0.0  0.000000    0.0    N  img_1.png   \n",
       "2   93689624             0       0.0 -0.035522    0.0    N  img_2.png   \n",
       "3   93689624             0       0.0 -0.035522    0.0    N  img_3.png   \n",
       "4   93689624             0       0.0 -0.035522    0.0    N  img_4.png   \n",
       "\n",
       "              Folder  \n",
       "0  data_raw/normal_1  \n",
       "1  data_raw/normal_1  \n",
       "2  data_raw/normal_1  \n",
       "3  data_raw/normal_1  \n",
       "4  data_raw/normal_1  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_path_raw_folders = [os.path.join(RAW_DATA_DIR, f) for f in DATA_FOLDERS]\n",
    "\n",
    "dataframes = []\n",
    "for folder in full_path_raw_folders:\n",
    "    current_dataframe = pd.read_csv(os.path.join(folder, 'airsim_rec.txt'), sep='\\t')\n",
    "    current_dataframe['Folder'] = folder\n",
    "    dataframes.append(current_dataframe)\n",
    "    \n",
    "dataset = pd.concat(dataframes, axis=0)\n",
    "\n",
    "print('Number of data points: {0}'.format(dataset.shape[0]))\n",
    "\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们首先给数据加上了文件夹位置。你将注意到在我们的数据集中有两类型的文件夹 - 'normal（直行）' 和 'swerve（转向）'。 他们分别代表不同的驾驶策略。我们来试着理解下这两种不同的驾驶风格。首先，我们将画出两种不同驾驶风格的一部分数据点。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BEIR8uFTabgTwfCI6jIgGAbwZwDd7rvkGgBcT0QIiGgJwEoC7yhas0wHWrgW2bgWUCv6u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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b085400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "min_index = 100\n",
    "max_index = 1100\n",
    "steering_angles_normal_1 = dataset[dataset['Folder'].apply(lambda v: 'normal_1' in v)]['Steering'][min_index:max_index]\n",
    "steering_angles_swerve_1 = dataset[dataset['Folder'].apply(lambda v: 'swerve_1' in v)]['Steering'][min_index:max_index]\n",
    "\n",
    "plot_index = [i for i in range(min_index, max_index, 1)]\n",
    "\n",
    "fig = plt.figure(figsize=FIGURE_SIZE)\n",
    "ax1 = fig.add_subplot(111)\n",
    "\n",
    "ax1.scatter(plot_index, steering_angles_normal_1, c='b', marker='o', label='normal_1')\n",
    "ax1.scatter(plot_index, steering_angles_swerve_1, c='r', marker='o', label='swerve_1')\n",
    "plt.legend(loc='upper left');\n",
    "plt.title('Steering Angles for normal_1 and swerve_1 runs')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Steering Angle')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以观察到这两种驾驶策略在这里显著的不同。蓝色点显示了直行驾驶策略，这时你期待的是报此你的转向角接近于零上下，这使得你几乎在道路上直线在行驶。\n",
    "\n",
    "转向形式策略使得汽车在道路上左右晃动。 这在训练端对端深度模型时非常重要，要时刻牢记。因为我们没有做任何特征工程，我们的模型几乎全部依赖于我们提供给它的带有它在被调用时所需要的必要信息的数据。因此，为了说明模型可能遇到的任何大的转向，或者赋予模型自己在走出道路之后重新回到道路的能力，我们必须提供给模型足够多的这种训练。因此，我们创造了这些额外的数据集来集中分析这些场景。一旦你完成了本文档，你可以只使用“直行”数据集重新训练任何东西来看看看你的汽车在扩充的时间里它无法保持在道路行驶。（*译者：扩充的时间指的是汽车在非直线行驶道路。因为只使用了直线行驶数据集训练，汽车对转向形式没有任何能力，所以无法在道路上保持形式。*）\n",
    "\n",
    "> **思考训练 0.3：**  \n",
    "你认为，针对转向角度预测场景，哪些其他的数据收集方法是有必要的？ 通常的自动驾驶是怎样做的？\n",
    "\n",
    "现在，我们看下不同类别的数据集的数据量。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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edDzplqVrtmLRApbfexOzn3X4iNP7Fz7EzKywzCo8m2X/uhaA0NJGsqKXpL+X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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b11f320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset['Is Swerve'] = dataset.apply(lambda r: 'swerve' in r['Folder'], axis=1)\n",
    "grouped = dataset.groupby(by=['Is Swerve']).size().reset_index()\n",
    "grouped.columns = ['Is Swerve', 'Count']\n",
    "\n",
    "def make_autopct(values):\n",
    "    def my_autopct(percent):\n",
    "        total = sum(values)\n",
    "        val = int(round(percent*total/100.0))\n",
    "        return '{0:.2f}%  ({1:d})'.format(percent,val)\n",
    "    return my_autopct\n",
    "\n",
    "pie_labels = ['Normal', 'Swerve']\n",
    "fig, ax = plt.subplots(figsize=FIGURE_SIZE)\n",
    "ax.pie(grouped['Count'], labels=pie_labels, autopct = make_autopct(grouped['Count']))\n",
    "plt.title('Number of data points per driving strategy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "所以，大概四分之一收集的数据是转向驾驶策略的，剩余部分是直行驾驶策略。我们也可以看到，我们有大约47000 个数据要处理。这看来不够，所以我们的深度网络层不能太深。\n",
    "\n",
    "> **思考训练 0.4**\n",
    "像很多机器学习领域的东西一样，这个想法在不同的类别混合很多不同数量的数据，只不过这里是某些特殊问题，只能通过试验和出错来优化。你能找到一种分割不同类别数据比我们更好的方法嘛？\n",
    "\n",
    "我们来看看这两种策略的标签的分布。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TfLSqPlBV9x9eIQDABrbisxGnc7aelNnI1iVJnpfkpCT3THJikjuMLBAAYCOb50HUH0ny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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b0e1ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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iagIA2Io25Rqyqjo2yX2TvHvVoiOTXLFi+sp8bWhLVZ1WVbuqatc111yzqDIBAIZYeCCr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x18f5be48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins = np.arange(-1, 1.05, 0.05)\n",
    "normal_labels = dataset[dataset['Is Swerve'] == False]['Steering']\n",
    "swerve_labels = dataset[dataset['Is Swerve'] == True]['Steering']\n",
    "\n",
    "def steering_histogram(hist_labels, title, color):\n",
    "    plt.figure(figsize=FIGURE_SIZE)\n",
    "    n, b, p = plt.hist(hist_labels.as_matrix(), bins, normed=1, facecolor=color)\n",
    "    plt.xlabel('Steering Angle')\n",
    "    plt.ylabel('Normalized Frequency')\n",
    "    plt.title(title)\n",
    "    plt.show()\n",
    "\n",
    "steering_histogram(normal_labels, 'Normal label distribution', 'g')\n",
    "steering_histogram(swerve_labels, 'Swerve label distribution', 'r')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以从上述两个图中看到：\n",
    "* **汽车直行时，转向角几乎总是零**。这存在一个很大的不平衡，如果这部分数据没有被下采样，模型将总是预测转向角为零，汽车将不能转向。\n",
    "* 当汽车在转向策略形式时，我们获取在直线行驶策略数据集中没有出现的大的转向。**这验证了我们上述解释过的收集这类型数据的原因**\n",
    "\n",
    "到这里，我们需要将所有的数据整合到压缩数据文件以适配训练。因此，我们使用.h5 文件，因为这个格式支持大数据集合，不需要立刻将任何东西读入内存。另外，Keras 无缝只吃该格式。\n",
    "\n",
    "接下来就直接处理处理数据，但需要一些时间。数据处理完成之后，最终的数据集将有4 部分：\n",
    "\n",
    "* image: 一个包含了图片数据的numpy 数组\n",
    "* previous_state: 一个包含了汽车上一个状态的numpy 数组。这是一个（转向，油门，制动，加速）元组\n",
    "* label: 一个包含了我们期待的要转向的转向角numpy 数组（格式化为-1 到 1这个范围）\n",
    "* metadata:一个包含了原始数据目录的numpy 数组（数据来自哪个文件夹等）\n",
    "\n",
    "这个处理需要一些时间。我们也会将数据分成train/test/validation 数据集。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_eval_test_split = [0.7, 0.2, 0.1]\n",
    "full_path_raw_folders = [os.path.join(RAW_DATA_DIR, f) for f in DATA_FOLDERS]\n",
    "Cooking.cook(full_path_raw_folders, COOKED_DATA_DIR, train_eval_test_split)#自建函数Cooking 就是数据处理.py 文件"
   ]
  },
  {
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   "metadata": {
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   },
   "source": [
    "我们现在准备开始构建我们的模型。请继续[next notebook](TrainModel.ipynb)来开始。"
   ]
  }
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